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GPT-5.5 Pro vs Kimi K2 Instruct (Fireworks): API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for GPT-5.5 Pro (OpenAI) and Kimi K2 Instruct (Fireworks) (Fireworks AI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.

Prices verified Apr 30, 2026

Interactive Cost Calculator

OpenAIGPT-5.5 ProFireworks AIKimi K2 Instruct (Fireworks)

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: Kimi K2 Instruct (Fireworks) at $18.50/month.

Cheapest: Kimi K2 Instruct (Fireworks) at $18.50/mo — save 98.5% vs GPT-5.5 Pro
Alert
BestKimi K2 Instruct (Fireworks)
Fireworks AI$18.50$0.001850$6.00$12.5098.5%Alerts coming soon
GPT-5.5 Pro
OpenAI$1,200.00$0.120000$300.00$900.00Alerts coming soon

Monthly Cost Comparison

Price Comparison at a Glance

All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.

Pricing TypeGPT-5.5 ProKimi K2 Instruct (Fireworks)Cheaper
Input (standard)$30.00/M$0.60/MKimi K2 Instruct (Fireworks)
Output$180.00/M$2.50/MKimi K2 Instruct (Fireworks)
Cached inputN/A$0.30/M
Batch inputN/A$0.30/M
Batch outputN/A$1.25/M

Prices last verified: 2026-03-10 – 2026-04-30

Cost Breakdown by Usage Volume

Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.

VolumeGPT-5.5 ProMonthlyKimi K2 Instruct (Fireworks)MonthlyGPT-5.5 ProPer requestKimi K2 Instruct (Fireworks)Per request
1K requests/mo$120.00$1.85$0.120000$0.001850
10K requests/mo$1,200.00$18.50$0.120000$0.001850
100K requests/mo$12,000.00$185.00$0.120000$0.001850
1M requests/mo$120,000.00$1,850.00$0.120000$0.001850

Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.

Price History

Input price per 1M tokens

When to Choose GPT-5.5 Pro

by OpenAI

  • General chatbot

Input / 1M tokens

$30.00/M

Output / 1M tokens

$180.00/M

Context window

1,050,000

Tier

premium

When to Choose Kimi K2 Instruct (Fireworks)

by Fireworks AI

  • Code generation
  • Document summarization
  • RAG / Semantic search

Input / 1M tokens

$0.60/M

Output / 1M tokens

$2.50/M

Context window

131,072

Tier

mid

Key Differences Beyond Price

Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.

CapabilityGPT-5.5 ProKimi K2 Instruct (Fireworks)
Context window1,050,000 tokens131,072 tokens
Max output tokens128,000 tokens16,384 tokens
Performance tierPremiumMid
Vision / image inputYesNo
Function callingYesYes
JSON modeYesYes
Prompt cachingNoYes
Batch API (50% discount)NoYes
Extended reasoningYesNo
Fine-tuningNoNo

Kimi K2 Instruct (Fireworks) notes

Fireworks serverless pricing. Cached input 50% discount. Batch at 50% of serverless.

Frequently Asked Questions

Is GPT-5.5 Pro cheaper than Kimi K2 Instruct (Fireworks)?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Kimi K2 Instruct (Fireworks) costs $185.00/month versus $12,000.00/month for GPT-5.5 Pro — a 98% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.

Which model has a larger context window, GPT-5.5 Pro or Kimi K2 Instruct (Fireworks)?

GPT-5.5 Pro has a larger context window at 1,050,000 tokens, compared to 131,072 tokens for Kimi K2 Instruct (Fireworks). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.

Do GPT-5.5 Pro and Kimi K2 Instruct (Fireworks) support the Batch API?

Kimi K2 Instruct (Fireworks) supports the Batch API (50% discount for async processing), while GPT-5.5 Pro does not. If your workload tolerates up to 24-hour latency, routing to Kimi K2 Instruct (Fireworks) with batch pricing could significantly cut costs versus GPT-5.5 Pro's standard rate.

Which model offers better prompt caching?

Kimi K2 Instruct (Fireworks) supports prompt caching at $0.30/M for cached input, while GPT-5.5 Pro does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Kimi K2 Instruct (Fireworks)'s caching capability can substantially reduce effective costs.

What are the best use cases for GPT-5.5 Pro vs Kimi K2 Instruct (Fireworks)?

GPT-5.5 Pro is best suited for General chatbot, while Kimi K2 Instruct (Fireworks) is optimized for Code generation, Document summarization, RAG / Semantic search. Choose based on which use case matches your primary workload — and validate with the cost calculator above to confirm the total monthly spend fits your budget.

What is the cost per request for GPT-5.5 Pro vs Kimi K2 Instruct (Fireworks)?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT-5.5 Pro costs $0.120000 per request and Kimi K2 Instruct (Fireworks) costs $0.001850 per request. At 100,000 requests/month, that translates to $12,000.00 and $185.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

GPT-5.5 Pro vs Kimi K2 Instruct (Fireworks): Summary

When comparing GPT-5.5 Pro and Kimi K2 Instruct (Fireworks) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Kimi K2 Instruct (Fireworks) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $185.00/month, compared to $12,000.00/month for GPT-5.5 Pro.

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT-5.5 Pro charges $30.00/M for input tokens and $180.00/M for output tokens. Kimi K2 Instruct (Fireworks) charges $0.60/M input and $2.50/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.

Prompt caching is supported by Kimi K2 Instruct (Fireworks) but not GPT-5.5 Pro. For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.

Context window capacity differs between the two: GPT-5.5 Pro supports up to 1,050,000 tokens in a single request, versus 131,072 tokens for Kimi K2 Instruct (Fireworks). A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.

Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

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Relevant Use Cases

See cost recommendations for workloads where GPT-5.5 Pro or Kimi K2 Instruct (Fireworks) is recommended.